The present invention relates to data center infrastructure, and more particularly, this invention relates to gathering statistics at servers and gateways to understand and manage overlay networks.
Network virtualization is an emerging data center and cloud computing trend which aims to virtualize a network as seen by end stations in a way that greatly simplifies network provisioning in multi-tenant environments, as well as traditional environments. One of the more common techniques of achieving network virtualization is to use network overlays, where tunnels are established between servers, edge network switches, and gateways to which end stations connect. The tunnel is actually implemented by encapsulating packets transmitted by a source end station into an overlay header that transports the packet from the source switch to a target switch in user datagram protocol (UDP) transport via an internet protocol (IP)-based network. The overlay header includes an identifier (ID) that uniquely identifies the virtual network. The target switch (tunnel end point) strips off the overlay header encapsulation, UDP transport header, and IP header, and delivers the original packet to the destination end station via conventional network connections. In addition to this tunneling mechanism, the edge switches participate in an address discovery protocol, which may be learning/flooding based, or lookup-based.
Overlay networks like Virtual eXtensible Local Area Network (VXLAN) connect geographically separated Layer-2 (L2) networks using tunnels. These are L2 over Laybr-3 (L3) tunnels. L2 packets originated by a virtual machine (VM) in a VXLAN and destined to another VM or group of VMs in same VXLAN in another physical location are carried over L3 tunnels.
However, current methods of collecting statistics to understand and manage network elements, such as those which conform to the Remote MONitoring (RMON) Management Information Base (MIB) and/or the Switch MONitoring (SMON) MIB are only capable of being implemented at an edge of an overlay network. This is because these methods of collecting statistics do not have the visibility to inner packets inside of overlay-encapsulated packets, and therefore there is a wealth of knowledge about the usage, distribution, and overall performance of network elements within an overlay network that is not able to be collected with conventional methods and approaches.